1. Field of The Invention
The present invention is generally directed to a method of extracting corresponding feature descriptive contours from a collection of images of slices of an object undergoing a repetitive motion cycle in response to an input of a seed contour proximate a feature contour in an image at given slice and motion cycle phase positions. In its more particular aspects, the present invention is directed to extracting such corresponding feature contours from magnetic resonance imaging (MRI) multi-image studies of the beating heart by automatic propagation of seed contours between images of different slices and/or between images of different phases.
2. Description of the Prior Art
MRI has become an invaluable medical diagnostic tool because of its ability to obtain high resolution in vivo images of a selected portion of the body, without invasion or use of ionizing radiation. In such imaging, a main magnetic field is applied longitudinally to an elongated generally cylindrical measurement space. The strength of this field determines the Larmor frequency of the relevant atomic nuclei (e.g. Hydrogen protons) to be excited. Sequences of radio frequency (rf) pulses, at or near this Larmor frequency, and magnetic field gradients are applied to the measurement space and resultant spin resonance signals, such as echo signals, are sampled. The collection of MR signal samples obtained from plural sequences applicable to the same slice are transformed in a processing unit, typically by Fourier transformation, to a two-dimensional array of pixel intensities which may be displayed on a display device or printed (typically to a film) as an image of the slice. It is common in MRI studies to make contemporaneous collections of MR signal data for plural images of the same body portion, such as parallel slices.
An interesting aspect of this imaging modality is that the image produced is not merely of the density of the relevant nuclei, but molecule type and/or motion dependent contrasts may be weighted as a function of the type and echo time of sequences utilized. For example, due to blood motion a spin-echo type sequence produces a "black blood" image because the relevant nuclei of the blood passing through the slice are not influenced by both excitation and echo rf pulses, while a small excitation angle fast gradient echo sequence produces a "white blood" image because the relevant nuclei of blood passing through the slice has not been depopulated of longitudinal magnetization spin states by prior excitation pulses.
The various configurations of the heart in its cycle of dilation and contraction are referred to as phases; these include the extremes of end of diastole and end of systole. Synchronizing information obtained from an electrocardiogram (ECG) is used either to trigger the evolution of the sequences for the desired phase(s) as in commonly owned U.S. Pat. No. 4,903,704 or as a means for sorting of MR signal samples obtained in a free running fashion as in U.S. Pat. No. 4,710,777. The image quality obtained varies dependent upon such conditions as echo time, phase position in the cardiac cycle and anotomic level of slice position, see P. Lanzer et al, "ECG-Synchronized Cardiac MR Imaging: Method and Evaluation", Radiology, Vol. 155, No. 2, June 1985, pp. 681-686.
Images for up to sixteen different phases are collectible with a cardiac package of Philips Medical Systems (Release 4.7, February 1988). After data for plural images representing multiple slices and multiple phases thereof are collected and supplied to an imaging workstation, the phases for a slice may be there displayed sequentially as a movie. Such movies for different slices may be displayed in side-by-side fashion.
Contour feature extraction from the cardiac image may be used for computational purposes such as computing a measure of the volume of the blood pool in a ventricle when the extracted contour is the inner heart wall (endocardium). An ejection fraction may then be computed from such ventricular volume measures of the end of diastole and end of systole phase positions.
In the aforementioned currently available package, the user "draws" on the image displayed by the workstation an outline of the edges of the cardiac chamber or wall of interest, a so-called irregular region of interest (IROI) by means of an input device, such as a trackball, redrawing as necessary until the user is satisfied that the contour drawn sufficiently matches the image contour feature of interest. Furthermore, IROI's may be stored in a data base for potential use with differently weighted images of the same phase and slice. Alternatively, the workstation may use a roughly drawn contour input by the user as a guide to an edge detection procedure which searches for an edge-detected contour near the rough contour. The contour produced by edge detection generally suffers from gaps, discontinuities in position or slope, multiplicities or other deficiencies which require editing or redrawing by the user. Because of these deficiencies and the differences between images at successive slice or phase positions, the contour produced by edge detection cannot serve as a rough contour for an adjoining slide or phase position without at least its prior review, and more generally, its modification, by the user.
An energy minimizing active contour function termed a "snake" has been proposed in M. Kass et al, "Snakes: Active Contour Models", International Journal of Computer Vision (1988), pp. 321-331, as a means for locking on to local features such as edges, and contours in an image and once locked on, tracking them in motion or matching them in stereopsis. An energy function is considered made up of the weighted sum of internal energy terms due to resistances to stretching and bending, image energy terms dependent on the type of feature the snake is to find, and external constraint energy terms, due to forces from such well behaved constructs as "springs" and point sources termed "volcanoes". The weighting of the resistances to stretching and bending indicate the degree to which the snake assumes a spatially smoothed contour. The "snake" active contour was further generalized in A. Amini et al, "Using Dynamic Programming for Minimizing the Energy of Active Contours in the Presence of Hard Constraints", Second International Conference on Computer Vision (Dec. 1988) pp. 95-99 to a dynamic programming in which the constraints imposed do not have to be spatially differentiable forces.